A Network Meta-analysis Comparing Exenatide Once Weekly with Other GLP-1 Receptor Agonists for the Treatment of Type 2 Diabetes Mellitus
Bibliographic record
Abstract
INTRODUCTION: Exenatide is a glucagon-like peptide-1 receptor agonist (GLP-1 RA), approved for treatment of type 2 diabetes mellitus (T2DM). There is limited direct evidence comparing the efficacy and tolerability of exenatide 2 mg once weekly (QW) to other GLP-1 RAs. A network meta-analysis (NMA) was conducted to estimate the relative efficacy and tolerability of exenatide QW versus other GLP-1 RAs for the treatment of adults with T2DM inadequately controlled on metformin monotherapy. METHODS: A systematic literature review was conducted to identify randomized controlled trials (RCTs) that investigated GLP-1 RAs (albiglutide, dulaglutide, exenatide, liraglutide, and lixisenatide) at approved doses in the United States/Europe, added on to metformin only and of 24 ± 6 weeks treatment duration. A Bayesian NMA was conducted. RESULTS: Fourteen RCTs were included in the NMA. Exenatide QW obtained a statistically significant reduction in glycated hemoglobin (HbA1c) relative to lixisenatide 20 µg once daily. No other comparisons of exenatide QW to other GLP-1 RAs were statistically significant for change in HbA1c. No statistically significant differences in change in weight, systolic blood pressure, risk of nausea or discontinuation due to adverse events were observed for exenatide QW versus other GLP-1 RAs. CONCLUSION: Exenatide QW demonstrated similar effectiveness and tolerability compared to other GLP-1 RAs, for the treatment of T2DM in adults inadequately controlled on metformin alone.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.059 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".